In the textile color quality control market, standard spectrophotometers have been used to measure fabric color for quality control and communication of color parameters. These spectrophotometers have worked well for solid color fabrics, but not for multi-color fabrics and prints. These materials, as well as heathers and fleece, have not been effectively measurable due to the averaging effect of spectrophotometers. Likewise, spectrophotometers do not perform well on multi-component materials such as garments with buttons and zippers or hardware components (e.g. car dashboards).
With the development of new multi or hyper spectral camera-based instruments, image capture and analysis of multi-color material is now possible. However, separating the color in many of the images has been difficult or impossible due to overlapping areas of color or indistinct color boundaries.
There are several well-known methods and techniques for color separation in an image. All of these methods, however, fail to provide an adequate color separation especially in images with overlapping areas of color or with indistinct color boundaries that are found in many textile samples.
Thus, what are therefore needed are systems and methods to identify and separate colors within images, where the images have overlapping areas of color or indistinct color boundaries. Furthermore, what are needed are systems and methods for evaluating the separated colors so as to reduce computational complexity and to speed up analysis.